function handles = initISCanalysis(handles)

% description/tag of the project:
PublicParams.dataDescription = 'movieData1';

% set paths:
PublicParams.maskPath = '/ISCtoolbox/templates/';
PublicParams.atlasPath = '/ISCtoolbox/templates/';
PublicParams.dataDestination = '/ISCresults/';

% Next, set source data file names for subjectSource -field. Full path 
% names must be given inside curly brackets (cell-format), where rows 
% present subjects and columns sessions,
% e.g (2 subjects and 2 scanning sessions):
%  PublicParams.subjectSource = 
%  [ {/fullpathname/subj1_ses1.nii}, {/fullpathname/subj1_ses2.nii}; 
%    {/fullpathname/subj1_ses2.nii}, {/fullpathname/subj2_ses2.nii} ]

PublicParams.subjectSource{1,1} = '/fMRIdata/Session1/preprocessed1.nii';
PublicParams.subjectSource{1,2} = '/fMRIdata/Session1/preprocessed2.nii';

% set data size for each scanning session in the form 
% [x y z t]. If this field is commented away, sizes 
% will be calculated automatically (in this case, files
% are temporally loaded into the Matlab to obtain size information).
%PublicParams.dataSize = [91 109 91 244];%91 109 91 382];

% set source file format either to 'mat' or 'nii':
PublicParams.fileFormatSubj = 'nii';

%%%%%%%%%%%%%%%%%%
% Settings regarding inter-subject synchronization:

% Select intersubject similarity criteria that are calculated:
PublicParams.ssiOn = 0; % sign-similarity index
PublicParams.nmiOn = 0; % mutual information based index
PublicParams.corOn = 1; % Pearson's correlation based index (recommended!)
PublicParams.kenOn = 0; % Kendall's W based index

% Determine parts of the analysis that will be performed:
PublicParams.calcStandard = 1; % standard analysis
PublicParams.calcStats = 0; % median, quartile, t and variance ISC maps
PublicParams.calcCorMatrices = 0; % save full correlation matrices
PublicParams.calcPhase = 0;

%%%%%%%%%%%%%%%%%%
% Frequency settings:

% set data sampling frequency:
PublicParams.samplingFrequency = (1/3.4);

% Set number of frequency subbands:
PublicParams.nrFreqBands = 3;

%%%%%%%%%%%%%%%%%% 
% Time-window settings:

% time-windowing on/off:
PublicParams.winOn = 0;
% Set window size and step size in samples. 
% Note: if windowSize exceeds time-series length,
% windowing is not used.
PublicParams.windowSize = 36;
PublicParams.windowStep = 9;

%%%%%%%%%%%%%%%%%%%%
% Template settings:
PublicParams.useTemplate = 1;

%%%%%%%%%%%%%%%%%%
% Permutation test settings. 
% To perform the following analysis, corOn must be set to 1.

% Set permutation parameters for frequency-specific ISC.
% To save time and memory, calculation can be done parallel
%  using several CPU:s (nrPermutationSets). Total 
% number of realizations in the "null distribution"
% will be: nrPermutationSets * nrPermutations (e.g. 10e7).
PublicParams.nrPermutationSets = 1;
PublicParams.nrPermutations = 10e5;

% Set permutation parameters for frequency-band comparison statistic. 
% Total number of realization in the "null distribution" will be
% nrPermutationsZPF * numberOfBrainVoxels
PublicParams.nrPermutationsZPF = 25000; % e.g. 25000

handles.Pub = PublicParams;
handles.validFlag = false;
handles.Priv = [];
handles.ParamsValid = false;